Enhancing Financial Security: Machine Learning with Block Chain for Fraud Detection

In the digital economy, financial fraud has become a serious issue to both people and organizations. It has become necessary to come up with fraud detection systems to avoid financial loss. Fraud detection is about finding and stopping dishonest actions where someone tries to cheat to get money or personal gain illegally. It involves spotting suspicious behavior and taking steps to prevent it. The financial fraudulence of today presents significant hurdles for traditional fraud detection systems, which often take very long to identify fraud and they rely on a single, fundamental database, leaving them subject to cyberattacks and single point of failure. The increasing issue of dealing these complicated fraudulent cases are too much for these systems to handle. In order to improve security, this paper propose an innovative approach that combines blockchain technology with machine learning (ML). Blockchain technology guarantees safe, transparent, and immutable storage of transaction data , reducing the risks of fraud, and machine learning algorithm LightGbm is used in the proposed system to detect the fraud in real-time based on the previous patterns. In addition to increased accuracy of fraud sensing, this hybrid architecture guarantees scalability, privacy, and fosters trust in digital financial transactions.